I am learning computer vision. When I was going through implementations of various computer vision projects, some OCR problems used GRU or LSTM, while some did not. I understand that RNNs are used only in problems where input data is a sequence, like audio or text.
So, in kernels of MNIST on kaggle almost no kernel has used RNNs and almost every repository for OCR on IAM dataset on GitHub has used GRU or LSTMs. Intuitively, written text in an image is a sequence, so RNNs were used. But, so is the written text in MNIST data. So, when exactly is it that RNNs(or GRUs or LSTMs) need to be used in computer vision and when don't?